Toward Enhanced Adversarial Robustness Generalization in Object Detection: Feature Disentangled Domain Adaptation for Adversarial Training

Toward Enhanced Adversarial Robustness Generalization in Object Detection: Feature Disentangled Domain Adaptation for Adversarial Training

Recent research has shown that deep learning models are likely to make incorrect predictions even when exposed to minor perturbations. To address this, training models on adversarial examples, particularly through Adversarial Training (AT), has gained attraction. However, traditional AT is prone to...

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Bibliographic Details
Main Authors: Yoojin Jung, Byung Cheol Song
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Adversarial robustness
adversarial training
domain adaptation
feature disentanglement
Online Access:https://ieeexplore.ieee.org/document/10769077/
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https://ieeexplore.ieee.org/document/10769077/

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